line and bar spurs graphs 2018 no answers

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P a g e |1
Name______________________________
Line & Bar Graphs
Line graphs show relationships between two variables or sets of data. In other words, they
show how one thing (variable) is affected by another variable and how the variables change
depending on one another. Line graphs are useful for showing trends in data and for making
predictions. They are very useful for showing trends over time; this means that they show how
one variable is affected by the other as the variable increases or decreases.
To make a quality line graph:
1. Put the independent (manipulated) variable on the X-axis. The X-axis is the horizontal
axis on the bottom of the graph.
2. Put the dependent (responding) variable on the Y-axis. The Y-axis is the vertical axis on
the side of the graph.
3. Decide on an appropriate scale for each axis. The scale is the numbers used on the axes
of the graph. The scale usually begins at zero. The scale of the graph is very important.
The same data can be plotted on different scales and not look like the same data at all.
4. Select an appropriate interval for your graph. The interval is the amount of space between
one number and the next or one type of data and the next on the graph. The interval is
just as important as the scale.
5. Label each axis.
6. Plot the data points.
7. Connect the data points with a line.
8. Give the graph a descriptive title that includes both variables. For example, Distance vs.
Time, Plant Height vs. Fertilizer Amount, etc.
One way to remember which data goes on which axis is DRY MIX
D- Dependent
M- Manipulated
R- Responding
I- Independent
Y- Y-axis
X- X-axis
M. V. Poarch 2018
science-class.net
Permission to copy granted for non-profit, educational use only.
P a g e |2
Bar graphs are used to show data that are not continuous. A bar graph allows us to compare
data like amounts or frequency or categories. They allow us to make generalizations and help
see differences in data. Bar graphs also let us find the value of one variable when we know the
value of the other.
To make a quality bar graph:
1. Put the independent (amounts, frequencies, categories) variable on the
X-axis. The X-axis is the horizontal axis on the bottom of the graph.
2. Put the dependent (what was measured) variable on the Y-axis. The Yaxis is the vertical axis
on the side of the graph.
3. Decide on an appropriate scale for each axis. The scale is the numbers used on the axes of
the graph. The scale usually begins at zero. Bar graphs frequently do not have numerical scales
on the X-axis. The scale of the graph is very important. The same data can be plotted on
different scales and not look like the same data at all.
4. Select an appropriate interval for your graph. The interval is the amount of space between
one number and the next or one type of data and the next on the graph. The interval is just as
important as the scale.
5. Label each axis.
6. For each of the specific independent variables (category, frequency, or amount) draw a solid
bar to height of appropriate dependent variable.
7. Give the graph a descriptive title that includes both variables
Remember, use a DRY MIX!
D- Dependent
M- Manipulated
R- Responding
I- Independent
Y- Y-axis
X- X-axis
M. V. Poarch 2018
science-class.net
Permission to copy granted for non-profit, educational use only.
P a g e |3
Practice making a quality line graph using the San Antonio Spurs wins by season in the table
below.
Then make a quality bar graph containing wins and losses.
Season
Wins
Losses
1997
20
62
1998
56
26
1999
37
13
2000
53
29
2001
58
24
2002
58
24
2003
60
22
2004
57
25
2005
59
23
2006
63
19
2007
58
24
2008
56
26
2009
54
28
2010
50
32
2011
61
21
2012
50
32
2013
58
24
2014
62
20
2015
55
27
2016
67
15
2017
61
21
M. V. Poarch 2018
science-class.net
Permission to copy granted for non-profit, educational use only.
P a g e |4
M. V. Poarch 2018
science-class.net
Permission to copy granted for non-profit, educational use only.
P a g e |5
M. V. Poarch 2018
science-class.net
Permission to copy granted for non-profit, educational use only.
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